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© 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Keith Blizard, Bob Tordella
October 2015
Self-service Cloud Services
How J&J Is Managing AWS at Scale
for Enterprise Workloads
ARC305
What to Expect from the Session
- Reviewing Enterprise Challenges & Incorporating Cloud Capabilities
- Provide approach for enabling Enterprise Controls
- Example Architecture & Implementations
- Example Patterns (HPC & Workspaces)
- Lessons Learned
J&J is a Global Health Care Leader
More than 270 Operating Companies in
60 Countries, with 126,000 employees
Selling Products in more than 175
Countries
The world’s sixth-largest consumer
health, pharmaceuticals, and biologics
company
The world’s largest medical devices and
diagnostics business
Big Company, Big Challenges
Thousands of
Systems
Complex IT Ops
Limited Financial
Impact
Cloud Patterns &
Acceleration
Automated IT Cost Transparency
Current State of Enterprise IT Cloud Strategy Offers Agility
Transformation to a Flexible Hybrid Cloud Strategy
N. America
DC
Provides complete infrastructure platform through
Amazon Web Services and integrated with J&J
processes and policies
On-Premise Cloud (OPCx)Virtual Private Cloud (VPCx)
Provides a highly flexible reference architecture (built
on VMware stack) to deliver ‘on-demand’ VMs inside
our Enterprise Data Centers or Co-location facilities
in each region
Europe
DC
AP DC
Compliance Data Protection Operation Transparency Speed + Agility
N. America
Region
Europe
Region
AP Region
Virtual Private Cloud (VPCx) Vision
Empower the business by providing an integrated, scalable, secure self-service cloud IT platform that
enables agility, enforces policy, and accelerates best practices
Enable Agility
• Self Service
• Rapid Provisioning
• Capacity Mgmt.
• Full stack Availability
Ensure Policy
• AD Integration
• J&J AMIs
• Enterprise Logging
• Backup & Retention
• Firewall & Security Rules
Accelerate Best
Practice
• Monitoring & Alerts
• VM Scheduling
• Encryption
• Software Config. Mgmt.
Enterprise Control without the Bottleneck
Preventative
Controls
Detective
Controls
Core principles for security,
compliance & management
Enforce Least
Privilege Approach
Log Everything
J&J Identity &
Group
Management
J&J Network
Extension
Enforce our
Images
Account Isolation
xbot
Big Data Account
Workspaces
Account
Xbot / Management Architecture
AWS Services
VPCx
Help
Assurance
Monitor
VPCx
DB
xbot
Admin
AD
Console
Billing
AWS
Console
Billing
Project Owners
VPCx Administrators
HPC Account
• Centralized Policy Enforcement - xbot
• Each Application Account is completely
isolated from each other
• Controls are executed through both
Assurance and Enforcement tests run
every 10 minutes
• Tickets are created for drift to
allowable values
Enterprise Control - Queue Management & Automation
Work
Queue
Work
Items
API Execution @
Each Account:
List, Info, Delete,
Update, Setup,
Admin, Login
Metadata:
Project Details,
Allowable Cloud Objects,
Chargeback,
Acceptable Values
Ex: HPC Account
Ticket
System
image = project.get_ec2_images(project_info['Id'], region, image_ids=image_id)
images = []
for img in image_objs:
unserialized_obj = binascii.a2b_qp(img['image'])
images.append(img)
instance_info[key][i.id]['Name']=i.tags.get('Name', '')
instance_info[key][i.id]['Env'] = i.tags.get('Environment', '')
instance_info[key][i.id]['Hostname'] = i.tags.get('Hostname', '')
instance_info[key][i.id][’ImageId'] = i.tags.get(’ami-id', ‘’)
If instance_info.img_id != allowable value
error.name = ‘instance-value-error’
error.value = instance_info
create_support_ticket(error.name=‘instance-value-error’)
Sample Control – Only Allowing Approved Images
Amazon DynamoDB – Project Metadata
Amazon DynamoDB – Project Level Exceptions
CLI – Automation – Member Info
User Level Information
And access list
CLI – Automation – Project Info
Project Lists including
account-code and
friendly name
CLI – Automation – Project Info
Project Metadata
Project Level Service
Listing
CLI – Automation – Adding Services
Adding New Service
for this Project
CLI – Automation – Project Info
New Service Added with
corresponding IAM
roles, policies
App AWS
Account
(002)
Core
Project
Services
Users
Alarms
HPC
App AWS
Account
(002)
Core
Project
Services
Users
Alarms
HPC
App AWS
Account
(002)
Core
Project
Services
Users
Alarms
HPC
AWS Account & Infrastructure Layer Control
Xbot Account
Payer
Account
(Consolidated
Billing)
Consolidated Billing
Xbot Administration
Scalable to 1000s of accounts
App AWS
Account
(001)
Core
Project
Services
Users
Alarms
HPC
App AWS
Account
(002)
Core
Project
Services
Users
Alarms
HPC
Core
Project
Services
Users
Alarms
HPC
Operating System & Database Layer Control
Xbot Account
App AWS Account (001)
RDS Amazon
Redshift
EC2
Operating System Database
Managing Amazon Redshift Controls
Encrypt
Sensitive Data
Work
Queue
Work
Items
Account Metadata:
Ex: HPC Account
Ticket
System
Checks 100s of
accounts every 10 min
for new instance;
enforces policy
AD Security
Group Sync
xbot
KMS
Sample Control ― Managing Redshift
audit policy requires:
# rotate_master_passwords=1hour
# apply_cw_metrics=95%CPUutil>60mins;85%DiskUsed>60mins;HealthStatus<1=10mins
# require_ssl=True
# enable_user_activity_logging=True; bucket_name=RegionalS3LogBucket
# backup_retention_period=35days
# modify_cluster(master_user_password=newpassword)
# publicly_accessible=False
# add_tags=‘Environment’;’Production’
# rotate_user_passwords=90days
# sync_users=(conn.rscluster)
## add users, set groups, revoke public schema
## drop users, move schema ownership
User Federates into Account
User creates Cluster
Cluster Created
Within 10 minutes,
xbot takes over
Master User
Master User
Password is reset by
xbot every hour
Master User takes over, abstracts
itself by syncing with AD Security
Groups tied to that AWS Account
Begins to build a Profile / Group
Grants various permissions to group
and associates DBAs
Revokes Access to Public Schema to
ensure least privilege
Xbot detects new Cluster;
applies CloudWatch Alarms
Alarms
Xbot enables logging & sets
the maximum backup retention
Xbot updates Parameter Group
for SSL & User Activity Logging
Xbot resets the
parameter group
within 10 minutes to
enforce policy
(ARC305) How J&J Manages AWS At Scale For Enterprise Workloads
Xbot notifies users of
the changes to their
environment
Enterprise Log Management
Queries logs
out of DB
Rotates logs
every week
Temp Location
for Log Movement
Elastic Load
Balancing
S3
Amazon
Redshift
Data Pipeline
EMR
CloudFrontCloudTrail Config
EC2
RDS
Regional S3
Logging Bucket
No API Action to
send DB user
Activity Logs to S3
Regional S3
Logging Bucket
Copies to S3
Bucket
(ARC305) How J&J Manages AWS At Scale For Enterprise Workloads
EC2 Elastic Load
Balancing
S3EBS Amazon
Glacier
RDS Amazon
Redshift
Compute Storage & Content Delivery Database
AWS Components Orchestrated
DynamoDB
Amazon
Kinesis
Data Pipeline
EMR
VPC Direct Connect
Auto Scaling
CloudFront ElastiCache
CloudFormation CloudWatchCloudTrail
IAM SESSNSCloudSearch SQSSWF Python (boto)
WorkSpacesWorkDocs
Directory
Service
Trusted
Advisor Config
Networking Management Tools
Enterprise Applications
Common Architecture Pattern for Big Data or HPC
us-east-1 (10.X.X.X/25)
us-east-1a
10.X.X.0/27
us-east-1b
10.X.X.32/27
Connected VPC
VPC Peering
Amazon S3
Win/Lin
EC2
DynamoDB
us-east-1 (10.X.X.X/19)
Disconnected VPC for EMR
IGW
us-east-1a
10.X.0.X/21
us-east-1b
10.X.7.X/21
us-east-1c
10.X.15.X/20
Burst High Performance Computing (HPC) workloads
in Private Address Space in same Account
Take advantage of multiple
subnets / AZs for Spot
Instance Pricing
Common Use Cases
• Statistical Analysis on large data sets; e.g.
Genomic Sequencing
• Transformations of large complex data sets for
Advanced Analytics (Sales & Supply Chain)
• Machine Learning engines on unstructured or
non-relatable data
Large volumes of
Structured & Unstructured
Data
Direct Connect
VGW
On-Premise Internal Data SourcesAdmins
OIA
J&J
DCs
JJNET
MFA
SCCM Site
& DP
J&J Resources J&J Facility
Zero Client
ELB
Workspaces Account
Infra Comp
Account
Core Infra Account Zero Client
Account
Teradici
Connection
Manager
Workspaces Architecture Patterns
Comments
• Global implementation across NA, EMEA and AP
• Infrastructure components living within AWS for scale,
performance and management
• J&J Network extended into AWS
Tradeoff / Lessons Learned
- DevOps is heavily recommended for approach to cloud. Focus on
velocity of new capabilities & operational improvements
- Security Engagement and Partnership is critical
- Identify, Design and remain Diligent with your Cloud Principles
- Early evaluation with CMP – focus has been too much on IaaS &
Provisioning only
- Partnership with 3rd Party is crucial (Log Management, Web
Application Firewall, Utilization & Spend)
- Training of Enterprise IT Users is critical
Key Takeaways
- Lean into PaaS services
- Enable agility of the cloud to your end users through self-service
- Automate your enterprise controls
- Unleash power of the cloud for small to large patterns
Thank you!
Contact Details:
Keith Blizard – kblizard@its.jnj.com
Bob Tordella - btordell@its.jnj.com
Remember to complete
your evaluations!

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(ARC305) How J&J Manages AWS At Scale For Enterprise Workloads

  • 1. © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Keith Blizard, Bob Tordella October 2015 Self-service Cloud Services How J&J Is Managing AWS at Scale for Enterprise Workloads ARC305
  • 2. What to Expect from the Session - Reviewing Enterprise Challenges & Incorporating Cloud Capabilities - Provide approach for enabling Enterprise Controls - Example Architecture & Implementations - Example Patterns (HPC & Workspaces) - Lessons Learned
  • 3. J&J is a Global Health Care Leader More than 270 Operating Companies in 60 Countries, with 126,000 employees Selling Products in more than 175 Countries The world’s sixth-largest consumer health, pharmaceuticals, and biologics company The world’s largest medical devices and diagnostics business
  • 4. Big Company, Big Challenges Thousands of Systems Complex IT Ops Limited Financial Impact Cloud Patterns & Acceleration Automated IT Cost Transparency Current State of Enterprise IT Cloud Strategy Offers Agility
  • 5. Transformation to a Flexible Hybrid Cloud Strategy N. America DC Provides complete infrastructure platform through Amazon Web Services and integrated with J&J processes and policies On-Premise Cloud (OPCx)Virtual Private Cloud (VPCx) Provides a highly flexible reference architecture (built on VMware stack) to deliver ‘on-demand’ VMs inside our Enterprise Data Centers or Co-location facilities in each region Europe DC AP DC Compliance Data Protection Operation Transparency Speed + Agility N. America Region Europe Region AP Region
  • 6. Virtual Private Cloud (VPCx) Vision Empower the business by providing an integrated, scalable, secure self-service cloud IT platform that enables agility, enforces policy, and accelerates best practices Enable Agility • Self Service • Rapid Provisioning • Capacity Mgmt. • Full stack Availability Ensure Policy • AD Integration • J&J AMIs • Enterprise Logging • Backup & Retention • Firewall & Security Rules Accelerate Best Practice • Monitoring & Alerts • VM Scheduling • Encryption • Software Config. Mgmt.
  • 7. Enterprise Control without the Bottleneck Preventative Controls Detective Controls Core principles for security, compliance & management Enforce Least Privilege Approach Log Everything J&J Identity & Group Management J&J Network Extension Enforce our Images Account Isolation
  • 8. xbot Big Data Account Workspaces Account Xbot / Management Architecture AWS Services VPCx Help Assurance Monitor VPCx DB xbot Admin AD Console Billing AWS Console Billing Project Owners VPCx Administrators HPC Account • Centralized Policy Enforcement - xbot • Each Application Account is completely isolated from each other • Controls are executed through both Assurance and Enforcement tests run every 10 minutes • Tickets are created for drift to allowable values
  • 9. Enterprise Control - Queue Management & Automation Work Queue Work Items API Execution @ Each Account: List, Info, Delete, Update, Setup, Admin, Login Metadata: Project Details, Allowable Cloud Objects, Chargeback, Acceptable Values Ex: HPC Account Ticket System
  • 10. image = project.get_ec2_images(project_info['Id'], region, image_ids=image_id) images = [] for img in image_objs: unserialized_obj = binascii.a2b_qp(img['image']) images.append(img) instance_info[key][i.id]['Name']=i.tags.get('Name', '') instance_info[key][i.id]['Env'] = i.tags.get('Environment', '') instance_info[key][i.id]['Hostname'] = i.tags.get('Hostname', '') instance_info[key][i.id][’ImageId'] = i.tags.get(’ami-id', ‘’) If instance_info.img_id != allowable value error.name = ‘instance-value-error’ error.value = instance_info create_support_ticket(error.name=‘instance-value-error’) Sample Control – Only Allowing Approved Images
  • 11. Amazon DynamoDB – Project Metadata
  • 12. Amazon DynamoDB – Project Level Exceptions
  • 13. CLI – Automation – Member Info User Level Information And access list
  • 14. CLI – Automation – Project Info Project Lists including account-code and friendly name
  • 15. CLI – Automation – Project Info Project Metadata Project Level Service Listing
  • 16. CLI – Automation – Adding Services Adding New Service for this Project
  • 17. CLI – Automation – Project Info New Service Added with corresponding IAM roles, policies
  • 18. App AWS Account (002) Core Project Services Users Alarms HPC App AWS Account (002) Core Project Services Users Alarms HPC App AWS Account (002) Core Project Services Users Alarms HPC AWS Account & Infrastructure Layer Control Xbot Account Payer Account (Consolidated Billing) Consolidated Billing Xbot Administration Scalable to 1000s of accounts App AWS Account (001) Core Project Services Users Alarms HPC App AWS Account (002) Core Project Services Users Alarms HPC
  • 19. Core
  • 22. Users
  • 24. HPC
  • 25. Operating System & Database Layer Control Xbot Account App AWS Account (001) RDS Amazon Redshift EC2 Operating System Database
  • 26. Managing Amazon Redshift Controls Encrypt Sensitive Data Work Queue Work Items Account Metadata: Ex: HPC Account Ticket System Checks 100s of accounts every 10 min for new instance; enforces policy AD Security Group Sync xbot KMS
  • 27. Sample Control ― Managing Redshift audit policy requires: # rotate_master_passwords=1hour # apply_cw_metrics=95%CPUutil>60mins;85%DiskUsed>60mins;HealthStatus<1=10mins # require_ssl=True # enable_user_activity_logging=True; bucket_name=RegionalS3LogBucket # backup_retention_period=35days # modify_cluster(master_user_password=newpassword) # publicly_accessible=False # add_tags=‘Environment’;’Production’ # rotate_user_passwords=90days # sync_users=(conn.rscluster) ## add users, set groups, revoke public schema ## drop users, move schema ownership
  • 28. User Federates into Account User creates Cluster
  • 29. Cluster Created Within 10 minutes, xbot takes over Master User Master User Password is reset by xbot every hour
  • 30. Master User takes over, abstracts itself by syncing with AD Security Groups tied to that AWS Account
  • 31. Begins to build a Profile / Group Grants various permissions to group and associates DBAs
  • 32. Revokes Access to Public Schema to ensure least privilege
  • 33. Xbot detects new Cluster; applies CloudWatch Alarms
  • 35. Xbot enables logging & sets the maximum backup retention
  • 36. Xbot updates Parameter Group for SSL & User Activity Logging Xbot resets the parameter group within 10 minutes to enforce policy
  • 38. Xbot notifies users of the changes to their environment
  • 39. Enterprise Log Management Queries logs out of DB Rotates logs every week Temp Location for Log Movement Elastic Load Balancing S3 Amazon Redshift Data Pipeline EMR CloudFrontCloudTrail Config EC2 RDS Regional S3 Logging Bucket No API Action to send DB user Activity Logs to S3 Regional S3 Logging Bucket Copies to S3 Bucket
  • 41. EC2 Elastic Load Balancing S3EBS Amazon Glacier RDS Amazon Redshift Compute Storage & Content Delivery Database AWS Components Orchestrated DynamoDB Amazon Kinesis Data Pipeline EMR VPC Direct Connect Auto Scaling CloudFront ElastiCache CloudFormation CloudWatchCloudTrail IAM SESSNSCloudSearch SQSSWF Python (boto) WorkSpacesWorkDocs Directory Service Trusted Advisor Config Networking Management Tools Enterprise Applications
  • 42. Common Architecture Pattern for Big Data or HPC us-east-1 (10.X.X.X/25) us-east-1a 10.X.X.0/27 us-east-1b 10.X.X.32/27 Connected VPC VPC Peering Amazon S3 Win/Lin EC2 DynamoDB us-east-1 (10.X.X.X/19) Disconnected VPC for EMR IGW us-east-1a 10.X.0.X/21 us-east-1b 10.X.7.X/21 us-east-1c 10.X.15.X/20 Burst High Performance Computing (HPC) workloads in Private Address Space in same Account Take advantage of multiple subnets / AZs for Spot Instance Pricing Common Use Cases • Statistical Analysis on large data sets; e.g. Genomic Sequencing • Transformations of large complex data sets for Advanced Analytics (Sales & Supply Chain) • Machine Learning engines on unstructured or non-relatable data Large volumes of Structured & Unstructured Data Direct Connect VGW On-Premise Internal Data SourcesAdmins OIA
  • 43. J&J DCs JJNET MFA SCCM Site & DP J&J Resources J&J Facility Zero Client ELB Workspaces Account Infra Comp Account Core Infra Account Zero Client Account Teradici Connection Manager Workspaces Architecture Patterns Comments • Global implementation across NA, EMEA and AP • Infrastructure components living within AWS for scale, performance and management • J&J Network extended into AWS
  • 44. Tradeoff / Lessons Learned - DevOps is heavily recommended for approach to cloud. Focus on velocity of new capabilities & operational improvements - Security Engagement and Partnership is critical - Identify, Design and remain Diligent with your Cloud Principles - Early evaluation with CMP – focus has been too much on IaaS & Provisioning only - Partnership with 3rd Party is crucial (Log Management, Web Application Firewall, Utilization & Spend) - Training of Enterprise IT Users is critical
  • 45. Key Takeaways - Lean into PaaS services - Enable agility of the cloud to your end users through self-service - Automate your enterprise controls - Unleash power of the cloud for small to large patterns
  • 46. Thank you! Contact Details: Keith Blizard – kblizard@its.jnj.com Bob Tordella - btordell@its.jnj.com